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Related Concept Videos

Three-Dimensional Force System01:30

Three-Dimensional Force System

In mechanical engineering, a three-dimensional force system is a system of forces acting in three dimensions, with forces applied along the x, y, and z coordinate axes. The three-dimensional force system is an important concept in mechanical engineering, as it allows engineers to understand and analyze the behavior of objects and structures in three dimensions. By understanding the forces acting on a system, engineers can design more efficient and effective mechanical systems that can withstand...
Depth Perception and Spatial Vision01:15

Depth Perception and Spatial Vision

Depth perception is the ability to perceive objects three-dimensionally. It relies on two types of cues: binocular and monocular. Binocular cues depend on the combination of images from both eyes and how the eyes work together. Since the eyes are in slightly different positions, each eye captures a slightly different image. This disparity between images, known as binocular disparity, helps the brain interpret depth. When the brain compares these images, it determines the distance to an object.
Differential Leveling01:12

Differential Leveling

Differential leveling is a precise method in surveying used to determine the elevation difference between two points. Its primary goal is to establish accurate vertical measurements to create level surfaces or grade lines critical for designing and constructing infrastructures such as roads, bridges, and buildings.The procedure for differential leveling begins with setting up and leveling the instrument at a point where the benchmark can be seen. The level rod is held on the benchmark (BM), and...
Computed Tomography01:10

Computed Tomography

Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
Divergence Theorem in 3D Space01:20

Divergence Theorem in 3D Space

In vector calculus, flux measures the total flow of a vector field through a surface. For a closed surface in three-dimensional space, this means measuring how much of the field passes outward through every point on the boundary. Directly calculating this flux can be difficult when the surface has a complicated or irregular shape. The Divergence Theorem provides a powerful alternative by relating surface flux to behavior inside the enclosed region.The Divergence Theorem states that the outward...
Three-Dimensional Force System:Problem Solving01:30

Three-Dimensional Force System:Problem Solving

A three-dimensional force system refers to a scenario in which three forces act simultaneously in three different directions. This type of problem is commonly encountered in physics and engineering, where it is necessary to calculate the resultant force on the system, which can then be used to predict or analyze the behavior of the object or structure under consideration.
To solve a three-dimensional force system, first resolve each force into its respective scalar components. Do this using...

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Updated: Jul 3, 2026

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
11:34

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

Published on: December 3, 2013

Real-time 3D shape sensing based on GPU-accelerated OFDR with dynamic sweep-range compensation.

Rongyi Shan, Shijie Li, Shizhu Sun

    Optics Express
    |July 2, 2026
    PubMed
    Summary
    This summary is machine-generated.

    A new fixed-range k-domain resampling (FR-KDR) method improves real-time 3D shape sensing using multicore fiber (MCF) and optical frequency domain reflectometry (OFDR). This technique significantly reduces strain error and enhances shape reconstruction accuracy.

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    Sample Drift Correction Following 4D Confocal Time-lapse Imaging
    10:04

    Sample Drift Correction Following 4D Confocal Time-lapse Imaging

    Published on: April 12, 2014

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    Last Updated: Jul 3, 2026

    High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
    11:34

    High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

    Published on: December 3, 2013

    Sample Drift Correction Following 4D Confocal Time-lapse Imaging
    10:04

    Sample Drift Correction Following 4D Confocal Time-lapse Imaging

    Published on: April 12, 2014

    Area of Science:

    • Optical Engineering
    • Fiber Optics
    • Sensing Technology

    Background:

    • Real-time 3D shape sensing systems often face challenges with accuracy and processing speed.
    • Multicore fiber (MCF) and optical frequency domain reflectometry (OFDR) offer potential for advanced sensing applications.
    • Dynamic compensation methods are crucial for improving the performance of these systems.

    Purpose of the Study:

    • To introduce and demonstrate a novel dynamic sweep-range compensation method, fixed-range k-domain resampling (FR-KDR).
    • To evaluate the performance of FR-KDR in a real-time 3D shape sensing system utilizing MCF and OFDR.
    • To analyze the impact of FR-KDR on strain accuracy, shape reconstruction, and system processing efficiency.

    Main Methods:

    • Implementation of the fixed-range k-domain resampling (FR-KDR) method for dynamic sweep-range compensation.
    • Utilizing multicore fiber (MCF) and optical frequency domain reflectometry (OFDR) for 3D shape sensing.
    • Deployment of FR-KDR and wavelength shift demodulation on a graphics processing unit (GPU) for parallel computation.

    Main Results:

    • Strain root mean square error (RMSE) was reduced from 13.98 µε to 1.27 µε under zero-strain conditions.
    • Successful reconstruction of both 2D and 3D shapes with maximum position deviations of 13.49 mm (2D) and 16.95 mm (3D) for a 700 mm MCF.
    • Achieved an update rate of 23.8 Hz at 5 mm spatial resolution with GPU acceleration, demonstrating significantly improved data-processing efficiency compared to CPU computation.

    Conclusions:

    • The FR-KDR method effectively compensates for dynamic sweep ranges in real-time OFDR systems.
    • The proposed system achieves high accuracy in strain measurement and shape reconstruction.
    • GPU parallel computation is vital for achieving high-speed, real-time operation of the 3D shape sensing system.